Titanic Survival Report #machinelearning #datascience #education #dataanalysis

🛳️ Titanic Survival Report

This project dives into the historical Titanic dataset to uncover the patterns behind passenger survival. Through data cleaning, visualization, and machine learning, it builds a predictive model and tells a compelling story of tragedy, resilience, and insight.

## 🎯 Objective

To analyze the Titanic dataset and identify key factors influencing survival using Python, data visualization, and machine learning. The goal is to present findings in a way that is both educational and emotionally resonant.

## 📂 Project Contents

- `Titanic_Survival_Report.ipynb`: Main analysis notebook
- `titanic.csv`: Dataset used (Kaggle Titanic dataset)
- `titanic_survival_model.joblib`: Saved logistic regression model
- `images/`: Folder for visualizations (optional)

## 🧪 Key Analyses

- Data cleaning and preprocessing
- Exploratory Data Analysis (EDA)
- Feature engineering
- Survival rate comparisons by gender, age, class, and family size
- Logistic Regression model with ~80% accuracy
- Model saved using `joblib` for future use

## 🛠️ Tools & Libraries

- Python (pandas, numpy, matplotlib, seaborn, scikit-learn)
- joblib (for model persistence)
- Google Colab (for execution)
- Streamlit (optional for deployment)

Видео Titanic Survival Report #machinelearning #datascience #education #dataanalysis канала Zahabia Ahmed